Conduct quantitative research with both financial risk modelling and statistical models to measure
liquidity constraints and counterparty risk in FX derivatives and structured products.
• Assist in developing and back-testing of Monte Carlo stochastic models for FX portfolio liquidity stress
tests in Python.
• Develop portfolio market risk and credit risk management models to assess portfolio risk tolerance and
drive business decisions.
• Evaluate and recommend effective financing and hedging strategies to limit portfolio exposure and
liquidity risk.
• Develop risk and performance metrics at both individual trade and portfolio levels.
• Produce comprehensive liquidity reports to facilitate executive-level decision making on company
liquidity reserve, capital financing and portfolio hedging strategies.
• Build Python models and algorithms to streamline analytic functions such as calculation of mark to
market for FX derivatives, portfolio sensitivity analysis, liquidity reports automation, etc.
• Build risk-based pricing models (e.g. liquidity risk, credit risk, swap risk, etc. - XVAs) to derive product
minimum spreads.
• Build statistical models to maximise product spreads by analysing corporate customers’ financials,
geographic data and historical hedging behaviour.
• Quantify trading costs with different banks such as bid-ask spreads, swap costs and margin posting
agreement.
• Embed model calculations in either excel pricing tools or Google Data Studio dashboards for the front
office.
• Recommend strategies and pricing for structuring complex FX derivative products (e.g. Cross currency
swap, options structures and deal-contingent forwards).
• Develop frameworks to evaluate the dealers’ profitability and performances.
• Familiarity with International Financial Reporting Standards (IFRS - valuations of FX derivatives).
• Assist the FP&A team with liquidity forecasts and budget preparation.